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    {
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     "name": "stdout",
     "text": "Help on function semilogy in module matplotlib.pyplot:\n\nsemilogy(*args, **kwargs)\n    Make a plot with log scaling on the y axis.\n    \n    Call signatures::\n    \n        semilogy([x], y, [fmt], data=None, **kwargs)\n        semilogy([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n    \n    This is just a thin wrapper around `.plot` which additionally changes\n    the y-axis to log scaling. All of the concepts and parameters of plot\n    can be used here as well.\n    \n    The additional parameters *base*, *subs*, and *nonpositive* control the\n    y-axis properties. They are just forwarded to `.Axes.set_yscale`.\n    \n    Parameters\n    ----------\n    base : float, default: 10\n        Base of the y logarithm.\n    \n    subs : array-like, optional\n        The location of the minor yticks. If *None*, reasonable locations\n        are automatically chosen depending on the number of decades in the\n        plot. See `.Axes.set_yscale` for details.\n    \n    nonpositive : {'mask', 'clip'}, default: 'mask'\n        Non-positive values in y can be masked as invalid, or clipped to a\n        very small positive number.\n    \n    Returns\n    -------\n    lines\n        A list of `.Line2D` objects representing the plotted data.\n    \n    Other Parameters\n    ----------------\n    **kwargs\n        All parameters supported by `.plot`.\n\n"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "help(plt.semilogy)"
   ]
  },
  {
   "source": [
    "在y轴上绘制对数比例图"
   ],
   "cell_type": "markdown",
   "metadata": {}
  }
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